Enhancement of Images using Morphological Transformation

TL;DR

This paper presents a novel image enhancement framework that combines morphological transformations and Weber's law to improve contrast and background detection in images with poor lighting, using MATLAB simulations.

Contribution

It introduces a new method integrating morphological operations with Weber's law for effective image enhancement and background detection.

Findings

Enhanced contrast in images with poor lighting

Effective background detection using morphological analysis

Comparison shows improved results over existing techniques

Abstract

This paper deals with enhancement of images with poor contrast and detection of background. Proposes a frame work which is used to detect the background in images characterized by poor contrast. Image enhancement has been carried out by the two methods based on the Weber's law notion. The first method employs information from image background analysis by blocks, while the second transformation method utilizes the opening operation, closing operation, which is employed to define the multi-background gray scale images. The complete image processing is done using MATLAB simulation model. Finally, this paper is organized as follows as Morphological transformation and Weber's law. Image background approximation to the background by means of block analysis in conjunction with transformations that enhance images with poor lighting. The multibackground notion is introduced by means of the opening by reconstruction shows a comparison among several techniques to improve contrast in images. Finally, conclusions are presented.